Digital imaging devices are becoming more common in the consumer marketplace, partly due to progressive price reductions. Digital imaging devices include not only standard digital cameras, but also PC-connected digital cameras and peripheral digital camera attachments. PC-connected digital cameras are cameras that are designed to be connected to and controlled by a host personal computer. These PC-connected digital cameras are also known as “web cams”. Peripheral digital camera attachments are personal digital assistant (PDA) accessories that can be attached to a PDA so that the PDA can function as a digital camera.
Digital imaging devices typically employ a single image sensor, either a charge coupled device (CCD) sensor or a complementary metal oxide semiconductor (CMOS) sensor, to digitally capture a scene of interest as raw image data. The raw image data are then processed using a number of image-capturing parameters, such as white balance, color saturation, contrast, brightness, hue and gamma correction. In most digital imaging devices, an algorithm is used to automatically adjust these image-capturing parameters based on, for example, statistical measurements of the raw image data. Although this algorithm usually produces acceptable images, there are situations when the algorithm fails to correctly adjust the image-capturing parameters, which may result in lower quality images.
A solution to resolving the above-described problem is to override the parameter-adjusting algorithm and to manually adjust the image-capturing parameters. As an example, for most PC-connected digital cameras, one or more image-capturing parameters may be manually adjusted using accompanying software running on the host computer. Thus, in situations when the parameter-adjusting algorithm fails to correctly adjust the image-capturing parameters, a user may manually adjust the image-capturing parameters using the accompanying software to subsequently capture images of desired quality.
A concern with using accompanying software to manually adjust the image-capturing parameters of a digital imaging device is that a typical camera user may have no idea how to adjust the image-capturing parameters to bring about a desired change in the captured images. Thus, the user may apply a trial-and-error technique to bring about the desired changes. However, the use of such a crude technique to adjust the image-capturing parameters will most likely be very time consuming.
Another solution to resolving the parameter-adjusting algorithm failure is to enhance the images after the images have been captured by the digital imaging device, i.e., post-processing of captured images. Thus, the post-processing image enhancements can compensate for the effects of the parameter-adjusting algorithm failure in the captured images. There are a number of post-processing software applications that can enhance captured images. One software application of interest is the post-processing software sold under the trademark PHOTOGENETICS from QBeo, Inc. The QBeo software is designed to help users improve the quality of captured images. This program modifies a given captured image and then shows the original image and the modified image side by side. The user then rates the two images and the program progressively refines the image in several iterations. Another software application of interest is the post-processing software sold under the trademark ADOBE PHOTOSHOP from Adobe Systems Incorporated. The Adobe software includes a feature that shows the user six versions of a current image for selection in which the color has been slightly adjusted in six different directions. When the user selects a modified image, the selected image becomes the new “current” image. The user can iterate until the current image cannot be further improved.
A concern with the use of post-processing software to correct the parameter-adjusting algorithm failure in the digital imaging device is that each individual captured image must be enhanced using the software. Thus, if multiple images are captured using, for example, an incorrect brightness setting, then each captured image must be individually processed using the post-processing software to compensate for the incorrect brightness setting. Clearly, a better solution to correct the parameter-adjusting algorithm failure is to adjust the image-capturing parameters of the digital imaging device to the proper settings.
In view of these concerns, there is a need for a digital imaging system and method for adjusting the image-capturing parameters of the system that allows the user to more intuitively adjust the parameters in an efficient manner.